ABSTRACT_CORE B The long-term health of the lung and other tissues is inextricably linked to the sustainability of the protein fold and its function. Fold and function are tightly coupled to the energetic health of the cell. This is achieved by the emerging paradigm of harmonization of cell function (DNA, RNA and protein) with protein homeostasis or proteostasis, a collection of integrated biological pathways that generate, maintain and repair the proteome. Efforts in the previous funding period revealed the importance of both proteostasis sensitive pathways and the mitochondria in management of the aging lung, pathways that are responsive to the life-span extending drug metformin that is thought to impact the function of mitochondrial complex I, and ISRIB, which our preliminary data suggests accelerates lung repair in a variety of injury models. In Core B, we will quantitatively track changes in proteostasis during recovery from influenza A-induced tissue injury using integrated bulk and single cell RNA-Seq, spatial transcriptomics and rigorous mass spectrometry (MS) approaches. We will apply these approaches to high quality flow cytometry sorted samples of lung, skeletal muscle and brain tissue from aged mice provided by Core C. Our computational groups at Northwestern and Scripps Research interact freely via shared electronic platforms. They will use these data to create a multi- dimensional understanding of the impaired recovery from influenza A infection in older animals. Core B will couple these powerful technologies with the genetic and pharmacologic studies the investigators propose to manipulate mitochondrial complex I function, the integrated stress response and ATF4 over the lifespan. We will support these important studies in aging biology by focusing on three Specific Aims: Aim 1: To provide bulk and single cell RNA-Seq and spatial transcriptomic data using flow-sorted cell populations and homogenized tissues provided by Core C. Aim 2: To provide mass spectroscopy analyses from flow-sorted cell populations obtained from the lung, brain and skeletal muscle of aged animals. Aim 3. To use advanced machine learning and system science tools to couple genetic and pharmacologic interventions during aging with multi-omic experimental data from aging animals. While the methods employed in this Core are inherently unbiased, we take advantage of the special expertise within this Core and the PPG to focus on proteostasis, macrophage biology and metabolism over the lifespan. By providing simultaneous RNA-Seq and proteomic analysis of alveolar type II cells, alveolar macrophages, Core B we will create a multi-omic genotype to phenotype map of tissue recovery after injury during aging that will be broadly applicable to other environmental challenges that limit healthspan.